Adaptive Correction of Radar Channel-to-Channel Time-Dependent Errors

ABSTRACT

Aspects of the disclosure are directed to adaptive correction of radar channel-to-channel time-dependent errors. In accordance with one aspect, the adaptive correction of radar channel-to-channel time-dependent errors includes transforming a digitized data flow to generate a transformed data flow; detecting the transformed data flow to generate a detected data flow; focusing the detected data flow to generate a focused data flow; and aligning the focused data flow to generate a corrected data flow. In one aspect, it may further include performing a direction of arrival (DOA) processing on the corrected data flow to generate a resolved data set, processing the resolved data set to generate a post-processed data set, radiating a transmit radar waveform, capturing a receive radar waveform related to the transmit radar waveform and generating the digitized data flow based on the receive radar waveform.

CLAIM OF PRIORITY

The present application is a continuation application of U.S. patentapplication Ser. No. 16/207,102 filed on Dec. 1, 2018 and entitledADAPTIVE CORRECTION OF AUTOMOTIVE RADAR CHANNEL-TO-CHANNELTIME-DEPENDENT ERRORS″ which claims priority to Provisional ApplicationNo. 62/593,252 entitled “ADAPTIVE CORRECTION OF AUTOMOTIVE RADARCHANNEL-TO-CHANNEL TIME-DEPENDENT ERRORS” filed Dec. 1, 2017, andassigned to the assignee, the entire contents of the prior applicationsare incorporated herein by reference as if fully set forth below in itsentirety and for all applicable purposes.

TECHNICAL FIELD

This disclosure relates generally to the field of adaptive correction ofsignal processing errors, and, in particular, to adaptive correction ofradar channel-to-channel time-dependent errors.

BACKGROUND

Radars, such as automotive radars, with multiple channels may below-cost mass-produced devices that have time-varying channel-to-channelphase and/or amplitude mismatches. These channel-to-channel mismatchesmay be caused by temperature sensitivity or other environmental changes,mechanical mounting issues, or other sources. Although automotive radarmanufacturers attempt to minimize and/or compensate for these effects onthe device performance, uncorrected channel-to-channel mismatchessometimes persist.

SUMMARY

The following presents a simplified summary of one or more aspects ofthe present disclosure, in order to provide a basic understanding ofsuch aspects. This summary is not an extensive overview of allcontemplated features of the disclosure, and is intended neither toidentify key or critical elements of all aspects of the disclosure norto delineate the scope of any or all aspects of the disclosure. Its solepurpose is to present some concepts of one or more aspects of thedisclosure in a simplified form as a prelude to the more detaileddescription that is presented later.

In one aspect, the disclosure provides techniques and apparatus relatingto adaptive correction of signal processing errors. Accordingly, amethod for adaptive correction of radar channel-to-channel timedependent errors includes transforming a digitized data flow to generatea transformed data flow; detecting the transformed data flow to generatea detected data flow; reformatting the detected data flow forautofocusing; focusing the detected data flow to generate a focused dataflow; and aligning the focused data flow to generate a corrected dataflow.

In one example, the method further includes performing a direction ofarrival (DOA) processing on the corrected data flow to generate aresolved data set. In one example, the method further includesprocessing the resolved data set to generate a post-processed data set.In one example, the method further includes radiating a transmit radarwaveform using one or more transmit antenna elements. In one example,the method further includes capturing a receive radar waveform relatedto the transmit radar waveform using one or more receive antennaelements. In one example, the method further includes generating thedigitized data flow based on the receive radar waveform.

In one example, the method further includes converting the transmitradar waveform into transmitted electromagnetic energy. In one example,the method further includes using one or more transmit elements forconverting the transmit radar waveform. In one example, the receiveradar waveform includes a scaled replica of the transmit radar waveformwith a time delay T (tau) and a Doppler shift v (nu) for an object ofinterest. In one example, the aligning the focused data flow includescorrecting one or more phase or amplitude of the focused data flow.

In one example, the method further includes using a complex scaling ofthe focused data flow. (none example, the complex scaling includesin-phase and quadrature components of the focused data flow. In oneexample, the complex scaling includes magnitude and phase components ofthe focused data flow.

Another aspect of the disclosure provides an apparatus for adaptivecorrection of radar channel-to-channel time dependent errors, the methodincluding a range/Doppler transformer to transform a digitized data flowto generate a transformed data flow; a detection processor, coupled tothe range/Doppler transformer, to detect the transformed data flow togenerate a detected data flow; an autofocus processor, coupled to thedetection processor, to reformat the detected data flow for autofocusingand to focus the detected data flow to generate a focused data flow; anda channel alignment processor, coupled to the autofocus processor, toalign the focused data flow to generate a corrected data flow.

In one example, the apparatus further includes a direction of arrival(DOA) processor, coupled to the channel alignment processor, to performa direction of arrival (DOA) processing on the corrected data flow togenerate a resolved data set. In one example, the apparatus furtherincludes a post-processor, coupled to the DOA processor, to process theresolved data set to generate a post-processed data set. In one example,the apparatus further includes one or more transmit antenna elements toradiate a transmit radar waveform.

In one example, the apparatus further includes one or more receiveantenna elements to capture a receive radar waveform related to thetransmit radar waveform. In one example, the apparatus further includesa radar transceiver, coupled to the one or more receive antenna elementsand the one or more transmit antenna element, to generate the digitizeddata flow based on the receive radar waveform.

In one example, the channel alignment processor aligns the focused dataflow by correcting one or more phase or amplitude of the focused dataflow, or by using a complex scaling of the focused data flow. In oneexample, the correcting one or more phase or amplitude or the complexscaling includes in-phase and quadrature components of the focused dataflow. In one example, the correcting one or more phase or amplitude orthe complex scaling includes magnitude and phase components of thefocused data flow.

These and other aspects of the disclosure will become more fullyunderstood upon a review of the detailed description, which follows.Other aspects, features, and implementations of the present disclosurewill become apparent to those of ordinary skill in the art, uponreviewing the following description of specific, exemplaryimplementations of the present invention in conjunction with theaccompanying figures. While features of the present invention may bediscussed relative to certain implementations and figures below, allimplementations of the present invention can include one or more of theadvantageous features discussed herein. In other words, while one ormore implementations may be discussed as having certain advantageousfeatures, one or more of such features may also be used in accordancewith the various implementations of the invention discussed herein. Insimilar fashion, while exemplary implementations may be discussed belowas device, system, or method implementations it should be understoodthat such exemplary implementations can be implemented in variousdevices, systems, and methods.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an example block diagram of an automotive radar inaccordance with the present disclosure.

FIG. 2 illustrates an example block diagram of an automotive radarseparated into radar antennas, a radar transceiver with a digitized dataflowing from the radar transceiver and a radar microcontroller.

FIG. 3 illustrates an example flow diagram for adaptive correction forradar channel-to-channel time-dependent errors.

DETAILED DESCRIPTION

The detailed description set forth below in connection with the appendeddrawings is intended as a description of various configurations and isnot intended to represent the only configurations in which the conceptsdescribed herein may be practiced. The detailed description includesspecific details for the purpose of providing a thorough understandingof various concepts. However, it will be apparent to those skilled inthe art that these concepts may be practiced without these specificdetails. In some instances, well known structures and components areshown in block diagram form in order to avoid obscuring such concepts.

While for purposes of simplicity of explanation, the methodologies areshown and described as a series of acts, it is to be understood andappreciated that the methodologies are not limited by the order of acts,as some acts may, in accordance with one or more aspects, occur indifferent orders and/or concurrently with other acts from that shown anddescribed herein. For example, those skilled in the art will understandand appreciate that a methodology could alternatively be represented asa series of interrelated states or events, such as in a state diagram.Moreover, not all illustrated acts may be required to implement amethodology in accordance with one or more aspects.

In one example, the present disclosure provides a process to adaptivelycompensate for channel-to-channel phase and/or amplitude mismatches in aradar through digital signal processing. For example, digital signalprocessing may include signal processing algorithms which transformsignals in radar channels to processed signals. If these mismatches arenot corrected, they may result in object angle measurement errors and/ora degradation of the radar antenna beam pattern. In one aspect, thepresent disclosure is applicable to automotive radars with multiplechannels, e.g., electronically scanned array automotive radars, MultipleInput Multiple Output (MIMO) automotive radars, and other variants ofautomotive radars possessing multiple channels for spatial diversity. Inanother example, the present disclosure is applicable to any radar withmultiple channels.

In one example, a radar produces a two-dimensional output in eachchannel, e.g., a radar image as a function of two dimensions, such asrange and Doppler offset. For example, the radar image may include aplurality of resolution cells, where a first dimension includes aplurality of range bins (e.g., range resolution cells) and a seconddimension includes a plurality of Doppler bins (e.g., Doppler resolutioncells). The present disclosure is designed to work even when multipleobjects are located in the same range bin, i.e., range resolution cell.One skilled in the art would understand that although automotive radarapplications are mentioned herein, other types of applications forcorrecting channel-to-channel phase and/or amplitude mismatches may bewithin the spirit and scope of the present disclosure.

FIG. 1 illustrates an example block diagram 100 of an automotive radarin accordance with the present disclosure. In FIG. 1, the flow of dataand signal processing through the automotive radar is shown via thearrows. Although only one transmit antenna element 110 is shown in FIG.1, one or more transmit antenna elements 110 may be used within thespirit and scope of the present disclosure. In one example, a transmitantenna element 110 radiates transmitted electromagnetic energy 111 froma radar transceiver to free space. Multiple receive antenna elements 120are illustrated in FIG. 1.

In one example, a receive antenna element 120 captures receivedelectromagnetic energy 121 from free space and sends it to a radartransceiver. A radar transceiver 130 is shown in FIG. 1. In one example,the radar transceiver 130 may be an automotive radar transceiver. In oneexample, the radar transceiver 130 may include a radar transmitter and aradar receiver. In one example, the radar transceiver 130 may generate atransmit radar waveform which is converted to the transmittedelectromagnetic energy 111 by the one or more transmit elements 110. Inone example, the radar waveform may be a coherent pulsed radar waveformwith a quantity of pulses over a coherent time duration.

In one example, the radar transceiver 130 may receive a receive radarwaveform from the received electromagnetic energy 112. In one example,the receive radar waveform is a scaled replica of the transmit radarwaveform. In one example, the receive radar waveform includes a scaledreplica of the transmit radar waveform with a time delay t (tau) and aDoppler shift v (nu) for an object of interest. A digitized data flow140 from each receive antenna element is shown in FIG. 1. In oneexample, the digitized data flow 140 is generated by ananalog-to-digital converter (ADC) 141 (not shown) which converts thereceive radar waveform to the digitized data flow 140 in the radartransceiver 130. In one example, the digitized data flow 140 may beindexed (i.e., labeled) as a function of delay index and a pulse index.In one example, the delay index maybe denoted as a fast time. In oneexample, the pulse index may be denoted as a slow time.

A range/Doppler transformer 150 or a similar data transformer of thedigitized data flow 140 is shown in FIG. 1. In one example, therange/Doppler transformer 150 performs range compression and Dopplerprocessing to convert the digitized data flow 140 to a transformed dataflow 160. For example, the transformed data flow 160 may be arange/Doppler array with a plurality of resolution cells. In oneexample, the plurality of resolution cells includes a first dimensionwhich may include a plurality of range bins (e.g., range resolutioncells) and a second dimension which may include a plurality of Dopplerbins (e.g., Doppler resolution cells).

In one example, a transformed data flow 160 is illustrated for eachreceive channel. In one example, the transformed data flow 160 includesa first transformation from delay index to a range index. In oneexample, the transformed data flow 160 includes a second transformationfrom pulse index to a Doppler index. In one example, the plurality ofresolution cells may be indexed by the range index and the Dopplerindex. In one example, the quantity of pulses over the coherent timeduration may determine a size of the Doppler resolution cells.

A detection processor 170 (e.g., a processor coupled to a memory unit)for thresholding, Constant False Alarm Rate (CFAR) detection, or similardetection operation is shown in FIG. 1. In one example, a detected dataflow 180 is a flow of range/Doppler detections flattened into aone-dimensional data stream. An autofocus processor 190 (e.g., aprocessor coupled to a memory unit), developed for performing asynthetic aperture radar (SAR) or inverse synthetic aperture radar(ISAR) autofocus algorithm, is shown in FIG. 1. In one example, thedetected data flow 180 from each receive channel replaces a rangedimension for the autofocus algorithm. In one example, the receivechannels replace a slow time dimension for the autofocus algorithm.

In one example, the autofocus algorithm focuses the detected data flow180. In one example, the focusing may remove arbitrary phase errors(e.g., low order phase errors, high order phase errors,temperature-dependent phase errors, etc.).

A focused data flow 191 for each receive channel is shown in FIG. 1. Achannel alignment processor 192 (e.g., a processor coupled to a memoryunit) for performing correction of receive channel phase and/oramplitude is also shown. In one example, correction of receive channelphase and/or amplitude is performed using a complex scaling of eachreceive channel to align the receive channels. In one example, channelalignment normalizes the receive channels in amplitude and adjusts thereceive channel in phase. In one example, the channel alignment is basedon channel estimates.

A corrected data flow 193 for each receive channel is shown in FIG. 1. Adirection of arrival (DOA) processor 194 (e.g., a processor coupled to amemory unit) for executing a DOA algorithm on the corrected data flow193 is shown. In one example, the DOA algorithm provides an angularestimate of an angular direction of an object of interest. In oneexample, the angular estimate is a boresight angle (i.e., an anglerelative to a receive antenna boresight). In one example, the angularestimate is a pair of angular dimensions (e.g., elevation/azimuth,spherical angles, direction cosines, etc.). In one example, a resolvedradar data set 195 is inputted into a post-processor 196. In oneexample, the resolved radar data set 195 includes the angular estimateof the angular direction of the object of interest. In one example, thepost-processor 196 may be a processor coupled to a memory unit. In oneexample, the post-processor 196 performs additional signal processing ofthe resolved radar data set 195.

As shown in the example of FIG. 1, one or more transmit antenna elements110 and multiple receive antenna elements 120 are connected to the radartransceiver 130. In one example, the radar transceiver 130 may includedigital to analog converters (DACs), upconverters, filters, amplifiers,passive components, low noise amplifiers, downconverters, analog todigital converters (ADCs), frequency synthesizers, oscillators, etc.Digitized signals from each receive channel may be processed inrange/Doppler transformer 150 into another domain (for example therange-Doppler domain) for each real receive channel or virtual receivechannel. In one example, a virtual receive channel is a synthesizedversion of a real receive channel.

In an example of a MIMO radar, range/Doppler transformer 150 may includeMIMO processing required to produce virtual receive channels. Forexample, consider a MIMO radar with three transmit channels and fourreal receive channels. MIMO processing contained in range/Dopplertransformer 150 may produce up to twelve virtual receive channels, forexample, by generating three virtual receive channels for every realreceive channels. Accordingly, the flows indicated by arrows labeled as160, 180, 191, and 195 may represent up to twelve virtual receivechannels rather than the four real receive channels.

For example, the transformed data flow 160 from each receive channel mayinclude preprocessing in detection processor 170 to mitigate the impactof a receiver noise level on the automotive radar. For example, thereceiver noise level may vary over space or over time or both. In oneexample, preprocessing in detection processor 170 may adaptively computea detection threshold. In one example, the detection threshold is aquantitative amplitude level which may be used to detect the object ofinterest in a resolution cell. In one example, detection may beindicated by a discrete level (e.g., TRUE/FALSE, Yes/No, Detect/NoDetect, etc.) for each resolution cell. The preprocessing performed indetection processor 170 may include thresholding, a Constant False AlarmRate (CFAR) detection, or possibly processing a machine learnedalgorithm to mitigate the impact of noise upon the automotive radar. Themultiple dimensional data processed in detection processor 170 (forexample range-Doppler data) may be then flattened into a separateone-dimensional data stream for each channel. For example, the detecteddata flow 180 (e.g., a flow of range/Doppler detections) may bereformatted into a flattened data stream, i.e., a one-dimensionaldetected data stream.

For example, a receive channel index may represent a second data domain(as represented by the arrows labeled as “180” exiting the detectionprocessor 170). The second data domain may be in a format that may beingested by a multitude of algorithms, which may be executed byautofocus processor 190, e.g., developed for autofocus of SyntheticAperture Radar (SAR) or Inverse Synthetic Aperture Radar (ISAR) data.The flattened data stream may take the place of the range domain and thereceive channel index may take the place of the slow time dimension. Inone example, the algorithms may include Phase Gradient Autofocus (PGA),Rank One Phase Error (ROPE) estimation, and/or various entropyminimization algorithms. Any one or more of such algorithms may beexecuted by autofocus processor 190.

For example, an advantage of SAR and ISAR processing algorithms may bethat they are robust and can readily process data with multiple objectswithin a range cell. If there are sufficient real or virtual receivechannels, a range line culling algorithm, for example, may detect thepresence of multiple scatterers in a range cell and thereby remove therange cell. In one example, removing the range cell may improve theperformance of algorithms that assume the presence of a single object inthe range cell, such as PGA or ROPE. Both PGA and ROPE may producemeaningless results if their input contains excessive noise dominatedrange-Doppler cells. The impact of these noise-dominated cells ismitigated by the processing of detection processor 170.

Since channel-to-channel errors (i.e., channel-channel mismatches) maybe time-dependent, the processing in channel alignment processor 192 maybe performed over fixed time dwells of data. In one example, a fixedtime dwell is a predetermined time duration. In one example, the fixedtime dwells may be chosen to be sufficiently long to produce ameaningful channel-to-channel error estimate without including a rapidvariation of the channel-to-channel mismatches. In one example, thefixed time dwells may range from 1 second to tens of seconds. In oneexample, the fixed time dwells may be chosen to provide sufficient timegranularity for the channel-to-channel relative phase and/or amplitudecorrected data flow 193 from each receive channel. In one example, theprocessing in autofocus processor 190 may be over non-overlappingsections in time or may be in some form of a sliding window.

In one example, the algorithms executed in autofocus processor 190 mayinclude a comparison of overall power in the receive channels to providea correction for channel-to-channel amplitude mismatches. In oneexample, the power comparison occurs following a thresholding or CFARprocess in detection processor 170 to minimize the impact ofrange-Doppler cells containing only noise.

In one example, the PGA, ROPE, or entropy minimization algorithmsexecuted in autofocus processor 190 may measure a linearchannel-to-channel phase error. In one example, the linearchannel-to-channel phase error may produce a beam pointing error.Accordingly, any linear phase produced from these algorithms may bemeasured and removed, or the corrected data flow 192 produced fromsubsequent blocks of time may be adjusted for a continuous linearadjustment.

Typically, another algorithm may be applied either in autofocusprocessor 190 or any processor to deduce the beam pointing error fromthe apparent motion of stationary objects (e.g., clutter returns)through the resulting range-Doppler-angle space. In one example, thecosine of the angle off boresight for each stationary object is equal tothe ratio of its apparent range rate to vehicle speed, and a fit to themeasured clutter motion may provide the beam pointing error. Thechannel-to-channel corrections are applied to the transformed data fromeach receive channel (real or virtual channel) in the channel alignmentprocessor 191. The channel-to-channel corrected data 192 then passes to(DOA) processor 193 for executing the direction of arrival algorithm.The resolved radar data set 195 (e.g., range-Doppler-angle data) thenpasses to post-processor 196 for further processing of the resolvedradar data set 195.

One skilled in the art would understand that although more than oneblock illustrated in FIG. 1 represents a processor, that the presentdisclosure of an automotive radar may include one processor or more thanone processor, and the one or more processor may be coupled to one ormore memory units.

In one example, the automotive radar continuously produces automatedupdates to mitigate against the antenna beam shape abnormalities due tothe time-dependent channel-to-channel phase and amplitude mismatches.The automated updates may be produced regardless of the vehicle motion,i.e., the updates may not require the vehicle to be in motion. In oneexample, there are two general types of antenna beam errors: beam shapeabnormalities due to nonlinear amplitude/phase errors and beam pointingerrors due to linear phase errors. A linear spatial dependence ofchannel-to-channel phase results in antenna beam pointing errors. Theautomotive radar may require vehicle motion to determine the beampointing errors due to this spatially dependent linear phase.Accordingly, the automotive radar may not update the linear phase whenthe vehicle is stationary.

FIG. 2 illustrates an example block diagram 200 of an automotive radarseparated into radar antennas, a radar transceiver with a digitized dataflowing from the radar transceiver and a radar microcontroller. FIG. 2also illustrates one or more transmit antenna elements 210. In oneexample, a transmit antenna element 210 radiates transmittedelectromagnetic energy from a radar transceiver to free space. Multiplereceive antenna elements 220 are shown in FIG. 2. In one example, areceive antenna element 220 captures received electromagnetic energy 221from free space and sends it to a radar transceiver. Although fourreceive antenna elements 220 are shown in FIG. 2, one skilled in the artwould understand that an example within the spirit and scope of thepresent disclosure may include fewer than four receive antenna elements220. Similarly, one skilled in the art would understand that an examplewithin the spirit and scope of the present disclosure may include morethan four receive antenna elements 220.

A radar transceiver 230 is shown in FIG. 2. In one example, the radartransceiver 230 may include a radar transmitter and a radar receiver. Inone example, the radar transceiver 230 may generate a transmit radarwaveform which is converted to the transmitted electromagnetic energy211 by the one or more transmit elements 210. In one example, the radartransceiver 230 may receive a receive radar waveform from the receivedelectromagnetic energy. In one example, the receive radar waveform is ascaled replica of the transmit radar waveform. In one example, thereceive radar waveform includes a scaled replica of the transmit radarwaveform with a time delay τ (tau) and a Doppler shift v (nu) for anobject of interest. In one example, the radar transceiver 230 produces adigitized data flow 240 for each receive antenna element 220. In theexample of FIG. 2, since four receive antenna elements 220 and onetransmit antenna element 210 are shown, four digitized data flows 240are shown. One skilled in the art would understand that as the quantityof receive antenna elements and/or transmit antenna elements vary, thequantity of digitized data flow may vary accordingly.

In one example, the digitized data flow 240 is sent to a microcontroller260. In one example, signal processing described in the FIG. 1 occurs inthe microcontroller 260. In one example, the microcontroller 260 may bea microprocessor, a digital signal processing chip, a general processingchip, etc. In one example, microcontroller 260 may include one or moreof the blocks illustrated in FIG. 1.

FIG. 3 illustrates an example flow diagram 300 for adaptive correctionfor radar channel-to-channel time-dependent errors. In block 310,radiate a transmit radar waveform, for example, using one or moretransmit antenna elements. In one example, the transmit radar waveformis from a radar transceiver. In one example, the transmit radar waveformis converted to transmitted electromagnetic energy by the one or moretransmit elements. In one example, the transmit radar waveform may be acoherent pulsed radar waveform with a plurality of pulses over acoherent time duration.

In block 320, capture a receive radar waveform related to the transmitradar waveform, for example, using one or more receive antenna elements.In one example, the receive radar waveform is sent to the radartransceiver. In one example, the receive radar waveform is a scaledreplica of the transmit radar waveform. In one example, the receiveradar waveform includes a scaled replica of the transmit radar waveformwith a time delay τ (tau) and a Doppler shift v (nu) for an object ofinterest.

In block 330, generate a digitized data flow based on the receive radarwaveform, for example, using a radar transceiver. In one example, thedigitized data flow may be indexed (i.e., labeled) as a function ofdelay index (e.g., fast time) and a pulse index (e.g., slow time).

In block 340, transform the digitized data flow to generate atransformed data flow, for example, using a range/Doppler transformer.In one example, the transformed data flow results from range compressionand Doppler processing to convert the digitized data flow to thetransformed data flow. For example, the transformed data flow may be arange/Doppler array with a plurality of resolution cells. In oneexample, the transformed data flow includes a first transformation fromdelay index to a range index. In one example, the transformed data flowincludes a second transformation from pulse index to a Doppler index. Inone example, the plurality of resolution cells may be indexed by therange index and the Doppler index.

In block 350, detect the transformed data flow to generate a detecteddata flow, for example, using a detection processor. In one example, thedetected data flow includes thresholding, Constant False Alarm Rate(CFAR) detection, or similar detection operation. In one example, thedetected data flow includes a flow of range/Doppler detections flattenedinto a one-dimensional data stream. In one example, the detected dataflow may be reformatted into a flattened data stream, i.e., aone-dimensional detected data stream.

In block 360, focus the detected data flow to generate a focused dataflow, for example, using an autofocus processor. In one example, thefocused data flow is produced using an autofocus algorithm. In oneexample, the detected data flow from each receive channel replaces arange dimension for the autofocus algorithm. In one example, the receivechannels replace a slow time dimension for the autofocus algorithm. Inone example, the autofocus algorithm generates focus parameters whichmay be used for channel alignment.

In block 370, align the focused data flow to generate a corrected dataflow, for example, using a channel alignment processor. In one example,the corrected data flow includes correction of receive channel phaseand/or amplitude. In one example, correction of receive channel phaseand/or amplitude is performed using a complex scaling of each receivechannel to align the receive channels. In one example, the complexscaling includes in-phase and quadrature components of the focused dataflow. In one example, the complex scaling includes magnitude and phasecomponents of the focused data flow.

In one example, channel alignment normalizes the receive channels inamplitude and adjusts the receive channel in phase. In one example, thechannel alignment is based on channel estimates. In one example, thechannel alignment may be based on focus parameters derived from theautofocus algorithm.

In block 380, perform a direction of arrival (DOA) processing on thecorrected data flow to generate a resolved data set, for example, usinga direction of arrival (DOA) processor. In one example, the resolveddata set includes an angular estimate of the object of interest. In oneexample, the angular estimate is a boresight angle (i.e., an anglerelative to a receive antenna boresight). In one example, the angularestimate is a pair of angular dimensions (e.g., elevation/azimuth,spherical angles, direction cosines, etc.).

In block 390, process the resolved data set to generate a post-processeddata set, for example, using a post-processor. In one example, thepost-processor 196 performs additional signal processing of the resolvedradar data set 195. In one example, the additional signal processingincludes data reduction or data compaction.

In one example, the term “to produce” as used in the present disclosuremay also be replace by the term “to generate” and still stay within thespirit and scope of the present disclosure. In one aspect, one or moreof the process or flow disclosed herein may be executed by one or moreprocessors which may include hardware, software, firmware, etc. The oneor more processors, for example, may include one or more memory units toexecute software or firmware needed to perform any part of the processor flow described herein. In one example, the memory unit may be one ormore of the following: a random access memory (RAM), a read only memory(ROM), a programmable ROM (PROM), an erasable PROM (EPROM), and/or anelectrically erasable PROM (EEPROM), etc.

In one example, for a hardware implementation, the processing units maybe implemented within one or more application specific integratedcircuits (ASICs), digital signal processors (DSPs), digital signalprocessing devices (DSPDs), programmable logic devices (PLDs), fieldprogrammable gate arrays (FPGAs), processors, controllers,micro-controllers, microprocessors, other electronic units designed toperform the functions described therein, or a combination thereof. Withsoftware, the implementation may be through modules (e.g., procedures,functions, etc.) that performs the functions described therein. Thesoftware codes may be stored in memory units and executed by a processorunit. Additionally, the various illustrative flow diagrams, logicalblocks, modules and/or algorithm steps described herein may also becoded as computer-readable instructions carried on any computer-readablemedium known in the art or implemented in any computer program productknown in the art.

Software shall be construed broadly to mean instructions, instructionsets, code, code segments, program code, programs, subprograms, softwaremodules, applications, software applications, software packages,routines, subroutines, objects, executables, threads of execution,procedures, functions, etc., whether referred to as software, firmware,middleware, microcode, hardware description language, or otherwise.

The software may reside on a computer-readable medium. Thecomputer-readable medium may be a non-transitory computer-readablemedium. A non-transitory computer-readable medium includes, by way ofexample, a magnetic storage device (e.g., hard disk, floppy disk,magnetic strip), an optical disk (e.g., a compact disc (CD) or a digitalversatile disc (DVD)), a smart card, a flash memory device (e.g., acard, a stick, or a key drive), a random access memory (RAM), a readonly memory (ROM), a programmable ROM (PROM), an erasable PROM (EPROM),an electrically erasable PROM (EEPROM), a register, a removable disk,and any other suitable medium for storing software and/or instructionsthat may be accessed and read by a computer.

The computer-readable medium may also include, by way of example, acarrier wave, a transmission line, and any other suitable medium fortransmitting software and/or instructions that may be accessed and readby a computer. The computer-readable medium may reside in the processingsystem, external to the processing system, or distributed acrossmultiple entities including the processing system. The computer-readablemedium may be embodied in a computer program product. By way of example,a computer program product may include a computer-readable medium inpackaging materials. The computer-readable medium may include softwareor firmware for performing any of the process or flow described herein.Those skilled in the art will recognize how best to implement thedescribed functionality presented throughout this disclosure dependingon the particular application and the overall design constraints imposedon the overall system.

What is claimed is:
 1. A method for adaptive correction of radarchannel-to-channel time-dependent errors, the method comprising:transforming a digitized data flow to generate a transformed data flow;detecting the transformed data flow to generate a detected data flow;reformatting the detected data flow for autofocusing; autofocusing thedetected data flow using phase gradient autofocus (PGA) to generate afocused data flow; and aligning the focused data flow to generate acorrected data flow.
 2. The method of claim 1, further comprisingperforming a direction of arrival (DOA) processing on the corrected dataflow to generate a resolved data set.
 3. The method of claim 2, whereina receive radar waveform includes a scaled replica of a transmit radarwaveform with a time delay τ (tau) and a Doppler shift v (nu) for anobject of interest.
 4. The method of claim 1, wherein the aligning thefocused data flow comprises correcting one or more phase of the focuseddata flow.
 5. A method for adaptive correction of radarchannel-to-channel time-dependent errors, the method comprising:transforming a digitized data flow to generate a transformed data flow;detecting the transformed data flow to generate a detected data flow;reformatting the detected data flow for autofocusing; autofocusing thedetected data flow using rank one phase estimation (ROPE) to generate afocused data flow; and aligning the focused data flow to generate acorrected data flow.
 6. The method of claim 5, further comprisingperforming a direction of arrival (DOA) processing on the corrected dataflow to generate a resolved data set.
 7. The method of claim 6, whereina receive radar waveform includes a scaled replica of a transmit radarwaveform with a time delay τ (tau) and a Doppler shift v (nu) for anobject of interest.
 8. The method of claim 5, wherein the aligning thefocused data flow comprises correcting one or more phase of the focuseddata flow.
 9. An apparatus for adaptive correction of radarchannel-to-channel time-dependent errors, the apparatus comprising: arange/Doppler transformer to transform a digitized data flow to generatea transformed data flow; a detection processor, coupled to therange/Doppler transformer, to detect the transformed data flow togenerate a detected data flow; an autofocus processor, coupled to thedetection processor, to focus the detected data flow using phasegradient autofocus (PGA) to generate a focused data flow; and a channelalignment processor, coupled to the autofocus processor, to align thefocused data flow to generate a corrected data flow.
 10. The apparatusof claim 9, further comprising a direction of arrival (DOA) processor,coupled to the channel alignment processor, to perform a direction ofarrival (DOA) processing on the corrected data flow to generate aresolved data set.
 11. The apparatus of claim 10, further comprising apost-processor, coupled to the DOA processor, to process the resolveddata set to generate a post-processed data set.
 12. The apparatus ofclaim 9, wherein the channel alignment processor aligns the focused dataflow by correcting one or more phase of the focused data flow, or byusing a complex scaling of the focused data flow.
 13. The apparatus ofclaim 12, wherein the correcting one or more phase or the complexscaling includes in-phase and quadrature components of the focused dataflow.
 14. The apparatus of claim 12, wherein the correcting one or morephase or the complex scaling includes magnitude and phase components ofthe focused data flow.
 15. An apparatus for adaptive correction of radarchannel-to-channel time-dependent errors, the apparatus comprising: arange/Doppler transformer to transform a digitized data flow to generatea transformed data flow; a detection processor, coupled to therange/Doppler transformer, to detect the transformed data flow togenerate a detected data flow; an autofocus processor, coupled to thedetection processor, to focus the detected data flow using rank onephase estimation (ROPE) to generate a focused data flow; and a channelalignment processor, coupled to the autofocus processor, to align thefocused data flow to generate a corrected data flow.
 16. The apparatusof claim 15, further comprising a direction of arrival (DOA) processor,coupled to the channel alignment processor, to perform a direction ofarrival (DOA) processing on the corrected data flow to generate aresolved data set.
 17. The apparatus of claim 16, further comprising apost-processor, coupled to the DOA processor, to process the resolveddata set to generate a post-processed data set.
 18. The apparatus ofclaim 15, wherein the channel alignment processor aligns the focuseddata flow by correcting one or more phase of the focused data flow, orby using a complex scaling of the focused data flow.
 19. The apparatusof claim 18, wherein the correcting one or more phase or the complexscaling includes in-phase and quadrature components of the focused dataflow.
 20. The apparatus of claim 18, wherein the correcting one or morephase or the complex scaling includes magnitude and phase components ofthe focused data flow.